An integrated linkage map reveals candidate genes underlying adaptive variation in Chinook salmon (Oncorhynchus tshawytscha)

Abstract

Salmonids are an important cultural and ecological resource exhibiting near worldwide distribution between their native and introduced range. Previous research has generated linkage maps and genomic resources for several species as well as genome assemblies for two species. We first leveraged improvements in mapping and genotyping methods to create a dense linkage map for Chinook salmon Oncorhynchus tshawytscha by assembling family data from different sources. We successfully mapped 14 620 SNP loci including 2336 paralogs in subtelomeric regions. This improved map was then used as a foundation to integrate genomic resources for gene annotation and population genomic analyses. We anchored a total of 286 scaffolds from the Atlantic salmon genome to the linkage map to provide a framework for the placement 11 728 Chinook salmon ESTs. Previously identified thermotolerance QTL were found to colocalize with several candidate genes including HSP70, a gene known to be involved in thermal response, as well as its inhibitor. Multiple regions of the genome with elevated divergence between populations were also identified, and annotation of ESTs in these regions identified candidate genes for fitness related traits such as stress response, growth and behaviour. Collectively, these results demonstrate the utility of combining genomic resources with linkage maps to enhance evolutionary inferences.

Linkage Mapping and Comparative Genomics of Red Drum (Sciaenops ocellatus) Using Next-Generation Sequencing

“…The total length of the consensus map (2105.30 cM) is larger than reported previously for the microsatellite-based map (1815.3 cM, Hollenbeck et al 2015); this difference is likely a result of combining maps from different families, using MERGEMAP, which is reported to inflate total map length (Khan et al 2012). Relative to the average total length of individual-based maps reported here, the total length of the consensus map was inflated by ∼24%, consistent with the results of McKinney et al (2015), who found that MERGEMAP increased the size of the Chinook salmon consensus map by ∼30% per additional family. However, there exists a tradeoff between accuracy of map lengths and inclusion of loci on the map (Hollenbeck et al 2015).…”

Salmonid chromosome evolution as revealed by a novel method for comparing RADseq linkage maps

“…Another recent approach compared a linkage map for the European tree frog Hyla arborea with the genome of the western clawed frog Xenopus tropicalis and identified many syntenic regions (Brelsford et al 2016). A recent approach in salmonids used a RADseq high-density linkage map for Chinook Salmon with the Atlantic Salmon reference genome to anchor Atlantic Salmon scaffolds to the Chinook Salmon linkage map when enough markers were present and the order was as expected (McKinney et al 2016). Homologous relationships between Chinook Salmon and Atlantic Salmon have been characterized previously (Brieuc et al 2014), and so the aligned scaffolds could then be classified as homologous, homeologous, or unsupported to further improve the anchoring of scaffolds onto the linkage map, and to identify potential genes around loci of interest (McKinney et al 2016).…”

Recent advances in conservation and population genomics data analysis

“…Despite this, having even a draft genome (in 1000s of scaffolds) can help improve data analyses in many ways including the following: (a) reliable discovery of SNPs (e.g., avoiding duplicated loci), (b) reducing genotyping error rates (Hand et al., 2015; Shafer et al., 2016), (c) detecting loci under selection by allowing sliding‐window approaches along scaffolds (Hohenlohe, Phillips, & Cresko, 2010), and (d) finding the underlying genes associated with phenotype or adaptation (facilitated by mapping scaffolds to related species with well‐annotated genomes; e.g., Ekblom & Wolf, 2014; Kohn, Murphy, Ostrander, & Wayne, 2006; McKinney et al., 2016). In addition, it is possible with this information to estimate effective population size ( N e ; e.g., Li & Durbin, 2011) or effective number of breeders ( N b ) using LD‐based methods, as comparisons can be restricted to pairs of loci on different scaffolds, which should reduce or eliminate LD due to physical linkage.…”